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Background: An accurate perception of death risk is a prerequisite for advanced cancer patients to make informed end-of-life care decisions. However, there is to date no suitable scale to measure death risk perception. This study was to develop and psychometrically test the death risk perception scale (DRPS) for advanced cancer patients. Methods: Process of instrument development and psychometric evaluation were used. First, qualitative research, a literature review, brainstorming, a Delphi study, and cognitive interviews were conducted to construct a pretest scale of death risk perception. Second, a scale-based survey was administered to 479 advanced cancer patients. Item, exploratory factor, and confirmatory factor analyses were employed to optimize the scale. The Cronbach's alpha was calculated as a reliability analysis. The validity analysis included construct, convergent, discriminant, and content validity values. Results: A three-dimension, 12-item scale was developed, including deliberative, affective, and experiential risk perception. The confirmatory factor analysis supported the three-factor model with satisfactory convergent and discriminant validity levels. The Cronbach's alpha coefficient for internal consistency was 0.807 and scale-level content validity index was 0.98. Conclusions: The 12-item DRPS is a reliable and valid instrument for assessing the level of death risk perception in advanced cancer patients. More studies are needed to examine its structure and robustness prior to use. [ABSTRACT FROM AUTHOR]

This review summarizes the best available evidence on the effects of death education in palliative care for cancer patients. A systematic literature review was conducted across 9 databases, revealing 22 eligible studies (N = 2,374). After two reviewers independently engaged in study selection, quality assessment, and data extraction, the results were synthesized through qualitative and quantitative analysis. Overall, the focus on death education for cancer patients showed an upward trend and consistently demonstrated significant positive effects with regards to the control of anxiety and depression, attitudes toward death, and quality of life. However, high-quality evidence regarding the effects of death education on cancer patients is lacking, warranting additional well-designed rigorous studies and standardized programs with specific and feasible steps. [ABSTRACT FROM AUTHOR]

Background: An accurate perception of death risk is a prerequisite for advanced cancer patients to make informed end-of-life care decisions. However, there is to date no suitable scale to measure death risk perception. This study was to develop and psychometrically test the death risk perception scale (DRPS) for advanced cancer patients. Methods: Process of instrument development and psychometric evaluation were used. First, qualitative research, a literature review, brainstorming, a Delphi study, and cognitive interviews were conducted to construct a pretest scale of death risk perception. Second, a scale-based survey was administered to 479 advanced cancer patients. Item, exploratory factor, and confirmatory factor analyses were employed to optimize the scale. The Cronbach's alpha was calculated as a reliability analysis. The validity analysis included construct, convergent, discriminant, and content validity values. Results: A three-dimension, 12-item scale was developed, including deliberative, affective, and experiential risk perception. The confirmatory factor analysis supported the three-factor model with satisfactory convergent and discriminant validity levels. The Cronbach's alpha coefficient for internal consistency was 0.807 and scale-level content validity index was 0.98. Conclusions: The 12-item DRPS is a reliable and valid instrument for assessing the level of death risk perception in advanced cancer patients. More studies are needed to examine its structure and robustness prior to use. [ABSTRACT FROM AUTHOR]

The fatigue behavior of large wind turbine blades is complex and stochastic due to their complex structure and operating environment. This paper focuses on developing a probabilistic fatigue life assessment method for wind turbine blades considering the uncertainties from wind velocity, material mechanical properties, pitch angle, and layer thickness. To improve the efficiency of stochastic fatigue behavior analysis of wind turbine blade, unidirectional fluid‐structure coupling (UFSC) and bidirectional fluid‐structure coupling (BFSC) analysis are employed to analyze the stochastic response. Then, Gaussian process regression (GPR) and Bayesian updating are combined to establish the stochastic fatigue behavior prediction model for wind turbine blade. On this basis, a modified S‐N curve formulation is proposed, and the fatigue life of wind turbine blade is analyzed by the modified S‐N curve and compared with the three‐parameter Weibull model. The results indicate that the proposed method for fatigue life assessment has better accuracy. The proposed probabilistic fatigue life assessment method with high accuracy and high efficiency, which is beneficial for the fatigue reliability design of wind turbine blades. [ABSTRACT FROM AUTHOR]

Microblade assemblages are among the most common prehistoric archaeological materials found on the Tibetan Plateau (TP) and are thought to indicate large scale migration to and settlement of the TP. Few microblade sites, however, have been systematically excavated, especially in the remotest, highest-elevation regions of the TP. The timing of the large-scale arrival, spread, and permanent settlement of people on the TP therefore remains controversial. In this paper, we report on a recently excavated site, Locality 3 of the Nwya Devu Site (ND3), located at 4600 meters above sea level (masl), near the shore of Ngoin Lake, on the interior TP. Our analyses reveal a fairly typical microblade technological orientation and two types of microblade cores: wedge-shaped and semi-conical, which are similar to those found throughout North China. Using Optically Stimulated Luminescence (OSL) dating and AMS 14C dating, the age of ND3 ranges from 11 to 10 ka. This date range indicates ND3 is the oldest microblade site yet recorded in the remote, high-elevation regions of the TP and thus provides important information about when and how hunter-gatherers using microblades began exploiting the higher altitudes of the TP. Taken together, studies at ND3 and throughout the TP suggest that a microblade adaptation is associated with the first prolonged human occupation of the plateau and that microblades played a significant role in mediating the risks and facilitating the mobility necessary to permanently inhabit the TP. [ABSTRACT FROM AUTHOR]

Cuproptosis and ferroptosis hold great promise for overcoming apoptotic resistance in liver cancer based on their unique metal‐driven cell death modalities. However, insufficient intracellular copper and iron concentration, complicated tumor microenvironment (TME), and unclear cross‐regulatory mechanisms between cuproptosis and ferroptosis, severely restrict the therapeutic performance. Herein, copper‐doped hollow Prussian blue (CHP) nanozymes are rationally designed for loading photosensitizer indocyanine green (ICG) and O2‐saturated perfluorohexane (PFH), denoted as O2‐PFH@CHPI nanoparticles, to induce cuproptosis and ferroptosis. In response to the specific TME, the CHP nanozymes can synergistically catalyze Fenton reactions and consume endogenous glutathione, leading to the accumulation of reactive oxygen species. Upon near‐infrared irradiation, the O2‐PFH@CHPI‐enabled photothermal effect can simultaneously accelerate catalytic reactions and trigger O2 release for photodynamic therapy to promote oxidative stress. Notably, cuproptosis can be effectively activated through Cu+‐mediated dihydrolipoamide S‐acetyltransferase aggregation and Fe–S cluster protein loss. Concurrently, the tilt of redox balance is favorable for lipid peroxidation and glutathione peroxidase 4 inactivation, resulting in an augmented ferroptosis effect. Mechanistically, oxidative stress‐boosted cuproptosis and ferroptosis jointly disrupt mitochondrial metabolism, which in turn exacerbates intracellular oxidative stress, thus realizing a mutually enhanced therapeutic effect. This work may provide new guidance for utilizing copper/ferrous‐engineering nanozymes for cuproptosis/ferroptosis synergetic therapy. [ABSTRACT FROM AUTHOR]

Hand, foot, and mouth disease (HFMD) caused by various enteroviruses is a major public health concern globally. Human enterovirus 71(EVA71), coxsackievirus A16 (CVA16), coxsackievirus A6 (CVA6), and coxsackievirus A10 (CVA10) are four major enteroviruses responsible for HFMD. Rapid, accurate, and specific point-of-care (POC) detection of the four enteroviruses is crucial for the prevention and control of HFMD. Here, we developed two multiplex high-fidelity DNA polymerase loop-mediated isothermal amplification (mHiFi-LAMP) assays for simultaneous detection of EVA71, CVA16, CVA6, and CVA10. The assays have good specificity and exhibit high sensitivity, with limits of detection (LOD) of 11.2, 49.6, 11.4, and 20.5 copies per 25 μL reaction for EVA71, CVA16, CVA6, and CVA10, respectively. The mHiFi-LAMP assays showed an excellent clinical performance (sensitivity 100.0%, specificity 83.3%, n = 47) when compared with four singleplex RT-qPCR assays (sensitivity 93.1%, specificity 100%). In particular, the HiFi-LAMP assays exhibited better performance (sensitivity 100.0%, specificity 100%) for CVA16 and CVA6 than the RT-qPCR assays (sensitivity 75.0–92.3%, specificity 100%). Furthermore, the mHiFi-LAMP assays detected all clinical samples positive for the four enteroviruses within 30 min, obviously shorter than about 1–1.5 h by the RT-qPCR assays. The new mHiFi-LAMP assays can be used as a robust point-of-care testing (POCT) tool to facilitate surveillance of HFMD at rural and remote communities and resource-limited settings. [ABSTRACT FROM AUTHOR]

Through an interesting physical perspective and a certain contraction of the Ricci curvature tensor in Finsler geometry, Akbar-Zadeh introduced the concept of scalar curvature for the Finsler metric. In this paper, we show that the Kropina metric is of isotropic scalar curvature if and only if F is an Einstein metric according to the navigation data. Moreover, we obtain the three-dimensional rigidity theorem for an Einstein–Kropina metric. [ABSTRACT FROM AUTHOR]

The timing and mechanisms of the human occupation of the demanding high-altitude Tibetan Plateau environment are of great interest. Here, we report on our reinvestigations and dating of the Nwya Devu site, located nearly 4600 meters above sea level on the central Tibetan Plateau. A new microblade techno-complex was identified on a lower lake shore at this site, distinct from the previously reported blade tool assemblage. These two lithic assemblages were dated to 45.6±2.6 and 10.3±0.5 ka using optically stimulated luminescence and accelerator mass spectrometry 14C methods. They represent, respectively, the earliest known Paleolithic and microlithic sites on the interior Tibetan Plateau, indicating multiple occupation episodes of hunter-gatherers during the past 45 ka. Our studies reveal that relatively stable depositional conditions and a paleoenvironment characterized by a comparatively warm climate facilitated these multiple occupations at Nwya Devu. The contemporaneous occurrence of the Upper Paleolithic blade technology on the Tibetan Plateau and most of Eurasia between 50 and 40 ka indicates rapid, large-scale dispersals of humans that profoundly affected human demography on a large scale. Combining new archaeological evidence and previously reported genetic data, we conclude that the Tibetan Plateau provided a relatively stable habitat for Upper Paleolithic hunter-gatherers, which may have contributed to the complex and multiple-origin gene pool of present-day Tibetans. [ABSTRACT FROM AUTHOR]

Thunderstorm high wind (THW) is defined as a kind of convective weather phenomenon with a maximum wind gust speed not less than 17.2 m·s−1 over China. It is a sudden, damaging, but common convective weather phenomenon during the warm seasons of China. By adopting a kernel density estimation (KDE) for the THWs during warm seasons (March–September) of 2010–2019 over eastern China and the European Centre for Medium-Range Weather Forecasts Reanalysis v5 (ERA5) dataset, the dry and wet THWs usually with different mechanisms are objectively obtained, and climatology and pre-convection environmental conditions investigated. KDE shows the total precipitable water (TPW) of 38 mm can be used as the threshold for distinguishing dry THWs from wet ones. Dry THWs mainly concentrate in North China and Yunnan province, while wet ones mainly concentrate in South China. West of Hebei province has high frequencies for both dry and wet THWs. A comparison of pre-convection environmental conditions shows dry THWs mainly occur under environmental conditions with lower saturation at both the middle-lower and upper layers, while wet ones usually have relatively lower saturation at the middle-lower layers. The instability of wet THWs can be well characterized by the most unstable lifted index (MULI) and most unstable convective available potential energy (MUCAPE), while dry ones can be well depicted by the lower 500 hPa temperature caused higher temperature difference (DT85) or temperature lapse rate (TLR85) between 850 and 500 hPa. The 0–6-km vertical wind shear (SHR6) can distinguish dry THWs from wet ones better than SHR1. The typical difference can be comprehensively revealed by the representative soundings. The results provide objective references for understanding and forecasting THWs under dry and wet environmental conditions. [ABSTRACT FROM AUTHOR]

Wheat stripe rust, triggered by Puccinia striiformis f. sp. tritici, is among the most widespread and damaging wheat (Triticum L.) diseases. The development of cultivars harboring adult plant resistance (APR) to stripe rust is a better approach to control the disease. The current study aimed to map APR to stripe rust via the QTL mapping of 165 F2–6 recombinant inbred lines (RILs), derivatives of Weimai 8/Zhengzhou 5389. The collection of phenotypic data for the stripe-rust resistance of both parents and all 165 RILs were conducted at Baoding, Hebei Province, during the 2016–2017 cropping seasons, and at Mianyang, Sichuan Province, during the 2017–2018 and 2018–2019 sowing seasons. The RIL populations and parents were also genotyped with 860 pairs of simple-sequence-repeat (SSR) primers to map APR QTLs to stripe-rust resistant. Moreover, a 55K SNP chip was used for small group bulk segregant analysis conducted to locate the genetic map location and concentration of the SNP markers on the wheat genome. Inclusive composite interval mapping (IciMapping 3.2) software identified four QTLs of stripe-rust resistance on chromosomes 1B, 2AS, 2BS, and 7DS, named QYr.wmy-1B, QYr.wmy-2AS, QYr.wmy-2BS, and QYr.wmy-7DS, which significantly explained 11.56–16.64%, 9.35–12.70%, 7.27–9.95%, and 11.49–15.07% of the phenotypic variation, respectively. All these QTLs were found from the resistant parent, Weimai 8. Meanwhile, the QTLs located on chromosomes 1B and 2AS were found close to Yr18 and Yr9, respectively. Furthermore, the results indicated that QYr.wmy-1B is possibly Yr9 and QYr.wmy-2AS is similar to Yr18 or might be a new QTL, whilst QYr.wmy-2BS and QYr.wmy-7DS were found to be different from previously reported stripe-rust-resistance QTLs and are possibly new QTLs. Overall, the QTLs and their closely associated molecular markers detected in this study could be a great source of input for marker-assisted selection to adult plant stripe-rust resistance in wheat-breeding programs. [ABSTRACT FROM AUTHOR]

Xylo-oligosaccharides (XOS) are considered as a promising type of prebiotics that can be used in foods, feeds, and healthcare products. Xylanases play a key role in the production of XOS from xylan. In this study, we conducted a metagenomic analysis of the fecal microbiota from dairy cows fed with different types of fodders. Despite the diversity in their diets, the main phyla observed in all fecal microbiota were Firmicutes and Bacteroidetes. At the genus level, one group of dairy cows that were fed probiotic fermented herbal mixture-containing fodders displayed decreased abundance of Methanobrevibacter and increased growth of beneficial Akkermansia bacteria. Additionally, this group exhibited a high microbial richness and diversity. Through our analysis, we obtained a comprehensive dataset comprising over 280,000 carbohydrate-active enzyme genes. Among these, we identified a total of 163 potential xylanase genes and subsequently expressed 34 of them in Escherichia coli. Out of the 34 expressed genes, two alkaline xylanases with excellent temperature stability and pH tolerance were obtained. Notably, CDW-xyl-8 exhibited xylanase activity of 96.1 ± 7.5 U/mg protein, with an optimal working temperature of 55 ℃ and optimal pH of 8.0. CDW-xyl-16 displayed an activity of 427.3 ± 9.1 U/mg protein with an optimal pH of 8.5 and an optimal temperature at 40 ℃. Bioinformatic analyses and structural modeling suggest that CDW-xyl-8 belongs to GH10 family xylanase, and CDW-xyl-16 is a GH11 family xylanase. Both enzymes have the ability to hydrolyze beechwood xylan and produce XOS. In conclusion, this metagenomic study provides valuable insights into the fecal microbiota composition of dairy cows fed different fodder types, revealing main microbial groups and demonstrating the abundance of xylanases. Furthermore, the characterization of two novel xylanases highlights their potential application in XOS production. [ABSTRACT FROM AUTHOR]

Background Method Results Conclusion Vitamin D (VD) is a neuroactive steroid involved in many brain functions, such as neurotrophic, neuroimmune control and neurotransmission, which affects the growth and function of the brain. The purpose of this study is to explore the effect of VD on motor and cognitive function of aged mice after sevoflurane anesthesia.We established sevoflurane anesthesia model and VD(-) and VD(+) mice model. The VD concentration of mice in each group was determined by enzyme-linked immunosorbent assay (ELISA). An open-field test was used to evaluate the mice’s capacity for movement and exploration. A Y-maze test was used to gauge the mice’s short-term memory. The primary purpose of the water-maze experiment was to examine mice’s long-term spatial memory.The ELISA results showed that the model was successfully constructed. In the open-field test, VD increased the exercise distance of mice (P < .05). In the Y-maze experiment, VD improved short-term memory impairment in mice (P < .05). In the water-maze test, VD increased the activity time and platform crossing number of mice in the target quadrant. (P < .05).Sevoflurane anesthesia caused cognitive dysfunction in aged mice, including reduced learning ability, memory loss, lower motor and exploratory abilities and depression, and VD deficiency aggravated these impairments. By supplementing with VD, learning ability and long-term memory were enhanced, motor and exploratory abilities were improved, and depression levels were reduced. Anxiety was also improved. [ABSTRACT FROM AUTHOR]

Epimedium is a classical Chinese herbal medicine, which has been used extensively to treat various diseases, such as sexual dysfunction, osteoporosis, cancer, rheumatoid arthritis, and brain diseases. Flavonoids, such as icariin, baohuoside I, icaritin, and epimedin C, are the main active ingredients with diverse pharmacological activities. Currently, most Epimedium flavonoids are extracted from Epimedium plants, but this method cannot meet the increasing market demand. Biotransformation strategies promised huge potential for increasing the contents of high-value Epimedium flavonoids, which would promote the full use of the Epimedium herb. Complete biosynthesis of major Epimedium flavonoids by microbial cell factories would enable industrial-scale production of Epimedium flavonoids. This review summarizes the structures, pharmacological activities, and biosynthesis pathways in the Epimedium plant, as well as the extraction methods of major Epimedium flavonoids, and advancements in the biotransformation and complete microbial synthesis of Epimedium flavonoids, which would provide valuable insights for future studies on Epimedium herb usage and the production of Epimedium flavonoids. [ABSTRACT FROM AUTHOR]

The class of warped product metrics can often be interpreted as key space models for the general theory of relativity and theory of space–time. In this paper, we study several non-Riemannian quantities in Finsler geometry. These non-Riemannian quantities play an important role in understanding the geometric properties of Finsler metrics. In particular, we find differential equations of Finsler warped product metrics with vanishing χ -curvature or vanishing H-curvature. Furthermore, we show that, for Finsler warped product metrics, the χ -curvature vanishes if and only if the H-curvature vanishes. [ABSTRACT FROM AUTHOR]

The class of warped product metrics can often be interpreted as key space models for the general theory of relativity and theory of space-time. In this paper, we first obtain the PDE characterization of Finsler warped product metrics with a vanishing Riemannian curvature. Moreover, we obtain equivalent conditions for locally Minkowski Finsler warped product spaces. Finally, we explicitly construct two types of non-Riemannian examples. [ABSTRACT FROM AUTHOR]

In this paper, we study conformal transformations between two almost regular general (α , β) -metrics. By using the method of special coordinate system, the necessary and sufficient conditions for conformal transformations preserving the mean Landsberg curvature are obtained. Further, a rigidity theorem for regular general (α , β) -metrics is proved. [ABSTRACT FROM AUTHOR]

In this paper, we study Kropina metrics with isotropic scalar curvature. First, we obtain the expressions of Ricci curvature tensor and scalar curvature. Then, we characterize the Kropina metrics with isotropic scalar curvature on by tensor analysis. [ABSTRACT FROM AUTHOR]

Gas turbine blades normally operate under high‐temperatures, extreme pressure, and high‐speed conditions, which leads to complex failure mechanisms and difficulties in fatigue life assessment. Moreover, due to the randomness of manufacturing errors, working loads, and material properties, the low cycle fatigue (LCF) life normally presents unavoidable stochastic behavior. Therefore, accurate and efficient fatigue life prediction is critical for the design of gas turbine blades. Accordingly, this paper analyzes the effects of mean stress, anisotropy, and uncertainties on the LCF life of nickel‐based single‐crystal turbine blades. The modified Hill yield criterion is employed to deal with the anisotropic damage characteristics of nickel‐based single‐crystal superalloy (NSCS) under a multiaxial stress state. Meanwhile, the effects of the temperature and crystal orientation are introduced into the walker mean stress correction term. A multiaxial LCF life prediction model is developed based on the energy criterion‐based fatigue life estimation method. Moreover, multi‐source uncertainties originating from rotation speeds, material properties, and temperature are analyzed and quantified. Comparison between the predicted and tested life indicates that the proposed method produces good accuracy and robustness, which can provide a reference for the reliability design of NSCS turbine blades. [ABSTRACT FROM AUTHOR]

Background: Cuproptosis is a regulated cell death form associated with tumor progression, clinical outcomes, and immune response. However, the role of cuproptosis in pancreatic adenocarcinoma (PAAD) remains unclear. This study aims to investigate the implications of cuproptosis-related genes (CRGs) in PAAD by integrated bioinformatic methods and clinical validation. Methods: Gene expression data and clinical information were downloaded from UCSC Xena platform. We analyzed the expression, mutation, methylation, and correlations of CRGs in PAAD. Then, based on the expression profiles of CRGs, patients were divided into 3 groups by consensus clustering algorithm. Dihydrolipoamide acetyltransferase (DLAT) was chosen for further exploration, including prognostic analysis, co-expression analysis, functional enrichment analysis, and immune landscape analysis. The DLAT-based risk model was established by Cox and LASSO regression analysis in the training cohort, and then verified in the validation cohort. Quantitative reverse transcriptase polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC) assays were performed to examine the expression levels of DLAT in vitro and in vivo, respectively. Results: Most CRGs were highly expressed in PAAD. Among these genes, increased DLAT could serve as an independent risk factor for survival. Co-expression network and functional enrichment analysis indicated that DLAT was engaged in multiple tumor-related pathways. Moreover, DLAT expression was positively correlated with diverse immunological characteristics, such as immune cell infiltration, cancer-immunity cycle, immunotherapy-predicted pathways, and inhibitory immune checkpoints. Submap analysis demonstrated that DLAT-high patients were more responsive to immunotherapeutic agents. Notably, the DLAT-based risk score model possessed high accuracy in predicting prognosis. Finally, the upregulated expression of DLAT was verified by RT-qPCR and IHC assays. Conclusions: We developed a DLAT-based model to predict patients' clinical outcomes and demonstrated that DLAT was a promising prognostic and immunological biomarker in PAAD, thereby providing a new possibility for tumor therapy. [ABSTRACT FROM AUTHOR]

The conformal transformation, which preserves Einstein metrics on Finsler warped product manifolds, is studied in this paper. We obtain sufficient and necessary conditions of a conformal transformation preserving Einstein metrics. In addition, we provide nontrivial examples of conformal transformations. Furthermore, we completely classify Einstein Riemannian warped product metrics and obtain the existence of a nontrivial conformal transformation that preserves Einstein metrics. [ABSTRACT FROM AUTHOR]

Graphene is one of the most prevailing materials to replace traditional transparent conductive films (TCFs). In order to improve the performance of graphene TCFs, it is proposed to directly deposit graphene on insulating substrates via assisted catalysis of Cu foil to avoid intricate transfer process, and further effectively enhance the optical performance by introducing the close‐packed antireflection array nanostructure. The graphene TCFs grown on bare quartz substrates have sheet resistance of 0.766 kΩ sq−1 and transmittance of 86.83 %. Graphene composite TCFs with transmittance of 95.79 % were obtained by introducing the close‐packed solid/hollow SiO2 nanospheres antireflection array nanostructure. Compared with graphene TCFs, transmittance of graphene composite TCFs increased significantly, while the sheet resistance remained at the same level. This method combining direct synthesis technique with novel antireflection array nanostructure provides a significant design idea to grow transfer‐free graphene with controllable optoelectronic properties and promotes the application and development of the future electronic devices. [ABSTRACT FROM AUTHOR]

Loop-mediated isothermal amplification (LAMP), as the rank one alternative to a polymerase chain reaction (PCR), has been widely applied in point-of-care testing (POCT) due to its rapid, simple, and cost-effective characteristics. However, it is difficult to achieve real-time monitoring and multiplex detection with the traditional LAMP method. In addition, these approaches that use turbidimetry, sequence-independent intercalating dyes, or pH-sensitive indicators to indirectly reflect amplification can result in false-positive results if non-specific amplification occurs. To fulfill the needs of specific target detection and one-pot multiplex detection, a variety of probe-based LAMP assays have been developed. This review focuses on the principles of these assays, summarizes their applications in pathogen detection, and discusses their features and advantages over the traditional LAMP methods. [ABSTRACT FROM AUTHOR]

In this paper, we identify the sufficient and necessary conditions for conformally related Randers metrics to have the same χ -curvature. Further, if s 0 = 0 holds, we conclude that the conformal transformation must be a homothety. Using the divergence theorem, we prove that, on the compact manifold, there is no nontrivial conformal transformation preserving the χ -curvature of the Randers metrics invariant. [ABSTRACT FROM AUTHOR]

Reliability of blades has a profound impact on both serviceability and safety of offshore wind turbines. Reliability estimation of wind turbine blade is a complex and time-consuming problem with multi-physics coupling and multi-failure modes correlation. Developing physics-of-failure modeling and reliability analysis methods with high efficiency and accuracy is a long-term challenge. In this work, a high availability and cost-effectiveness reliability estimation framework for offshore wind turbine blade by combining transfer learning (TL) and direct probability integral method (DPIM) is proposed. Extensive performance simulation of offshore wind turbine blade is a complex and necessary task, this paper develops a new adaptive sampling strategy to improve the validity of sample selection in the design space; On this basis, a physics-of-failure surrogate modeling approach is proposed by introducing TL method to fuse two kinds of multi-physics coupling analysis data, then the performance of all critical loads can be predicted efficiently in advance to provide a reliable design; Further, this paper provides an efficient reliability estimation method for offshore wind turbine blades by combining DPIM and surrogate model. Finally, the validity of the proposed approach is illustrated by numerical example and offshore wind turbine blade reliability estimation. The proposed framework provides a cost-effective alternative to higher loads simulation efforts and safety factors selection. • A new adaptive sampling strategy for multi-failure modeling is proposed. • A failure modeling method is developed for multi-physics coupling system. • A reliability estimation method is proposed based on Dirac delta function. [ABSTRACT FROM AUTHOR]

Ship instance segmentation in synthetic aperture radar (SAR) images can provide more detailed location information and shape information, which is of great significance for port ship scheduling and traffic management. However, there is little research work on SAR ship instance segmentation, and the general accuracy is low because the characteristics of target SAR ship task, such as multi-scale, ship aspect ratio, and noise interference, are not considered. In order to solve these problems, we propose an idea of scale in scale (SIS) for SAR ship instance segmentation. Its essence is to establish multi-scale modes in a single scale. In consideration of the characteristic of the targeted SAR ship instance segmentation task, SIS is equipped with four tentative modes in this paper, i.e., an input mode, a backbone mode, an RPN mode (region proposal network), and an ROI mode (region of interest). The input mode establishes multi-scale inputs in a single scale. The backbone mode enhances the ability to extract multi-scale features. The RPN mode makes bounding boxes better accord with ship aspect ratios. The ROI mode expands the receptive field. Combined with them, a SIS network (SISNet) is reported, dedicated to high-quality SAR ship instance segmentation on the basis of the prevailing Mask R-CNN framework. For Mask R-CNN, we also redesign (1) its feature pyramid network (FPN) for better small ship detection and (2) its detection head (DH) for a more refined box regression. We conduct extensive experiments to verify the effectiveness of SISNet on the open SSDD and HRSID datasets. The experimental results reveal that SISNet surpasses the other nine competitive models. Specifically, the segmentation average precision (AP) index is superior to the suboptimal model by 4.4% on SSDD and 2.5% on HRSID. [ABSTRACT FROM AUTHOR]

Aster tataricus (L.) is an important medicinal plant in China. Its roots are rich in flavonoids, the main medicinal components. However, the molecular basis of flavonoid biosynthesis in the roots of A. tataricus remains unclear. In this study, the content of total flavonoid of A. tataricus roots at different developmental stages was measured first, and the results showed that the content of total flavonoid gradually decreased from September to November, which may be caused by the stagnation of A. tataricus growth due to the decrease in temperature after September. Then, an integrated analysis of transcriptome and metabolome was conducted on five developing stages of A. tataricus roots to identify flavonoid compositions and potential genes involved in flavonoid biosynthesis. A total of 80 flavonoid metabolites, of which 75% were flavonols and flavonoids, were identified in metabolomic analyses, among which isorhamnetin, kaempferol, quercetin, and myricetin were the main skeletons of these flavonoids. Cluster analysis divided these 80 flavonoids into 3 clusters. The compounds in cluster I mainly accumulated in S1, S3, and S5. In cluster II, the relative content of the flavonoid metabolites showed an upward trend from S2 to S4. In cluster III, the flavonoids decreased from S1 to S5. A total of 129 structural genes, including 43 PAL, 23 4CL, 9 C4H, 4 CHS, 18 CHI, 3 F3H, 5 F3'H, 1 F3′5′H, 21 FLS, and 2 FSII, and 65 transcription factors, including 22 AP2/ERF, 7 bHLH, 5 bZIP, 8 MYB, 11 NAC, and 12 WRKY, showed significant correlation with total flavonoid content. Eighteen genes (7 4CL, 5 C4H, 2 CHI, 1 F3H, and 3 FLS) and 30 genes (5 PAL, 9 4CL, 1 C4H, 2 CHI, 1 F3H, 1 DFR, 7 3AT, 1 BZ1, and 3 UGT79B1) were identified as key structural genes for kaempferol and anthocyanins biosynthesis, respectively. Our study provides valuable information for understanding the mechanism of flavonoid biosynthesis in A. tataricus root. [ABSTRACT FROM AUTHOR]

Compressed sensing (CS) algorithms mostly achieve linear array synthetic aperture radar (LASAR) 3D sparse imaging under the On-Grid strategy, they suffer from the mismatch measurement matrix and decreased imaging quality due to the position-errors among targets and preset scattering units. Aimed at this problem, based on the Off-Grid strategy, a sparse recovery algorithm via adaptive grids (SRAG) is proposed in this paper. First, the proposed algorithm extracts the target scattering units in the imaging scene under the On-Grid strategy. Second, the target scattering units with position-errors are extracted under the non-zero adjacent scattering coefficient criterion, and they are defined as the unfocused scattering units. Third, according to whether the unfocused scattering units' distance is smaller than the scattering unit spacing, their search-areas of targets' real positions are set, respectively, and differently. Finally, based on the minimum scattering coefficient residual criterion, we adaptively compensate the unfocused scattering units' position-errors and re-estimate their scattering coefficients. Both simulation and experimental results indicate that the SRAG algorithm decreases the position-errors effectively, it improves the imaging quality, estimation accuracy of targets' positions, and scattering coefficients than traditional On-Grid CS algorithms. [ABSTRACT FROM AUTHOR]

Hepatocellular carcinoma (HCC) is one of the most common malignancies with high morbidity and mortality. Beta-1,3-galactosyltransferase 5 (b3galt5) plays crucial roles in protein glycosylation, but its function in HCC remains unclear. Here, we investigated the role and underlying mechanism of b3galt5 in HCC. We found that b3galt5 is highly expressed and associated with a poor prognosis in HCC patients. In vitro studies showed that b3galt5 promoted the proliferation and survival of HCC cells. We also demonstrated that b3galt5 deficiency suppressed hepatocarcinogenesis in DEN/TCPOBOP-induced HCC. Further investigation confirmed that b3galt5 promoted aerobic glycolysis in HCC. Mechanistically, b3galt5 promoted glycolysis by activating the mTOR/p70s6k pathway through O-linked glycosylation modification on mTOR. Moreover, p70s6k inhibition reduced the expression of key glycolytic enzymes and the glycolysis rate in b3galt5-overexpressing cells. Our study uncovers a novel mechanism by which b3galt5 mediates glycolysis in HCC and highlights the b3galt5-mTOR/p70s6k axis as a potential target for HCC therapy. [ABSTRACT FROM AUTHOR]

Background: The T helper 17 (Th17)/T regulatory (Treg) cell imbalance is involved in the course of obesity and type 2 diabetes mellitus (T2DM). In the current study, the exact role of glucagon-like peptide-1 receptor agonist (GLP-1RA) exenatide on regulating the Th17/Treg balance and the underlying molecular mechanisms are investigated in obese diabetic mice model. Methods: Metabolic parameters were monitored in db/db mice treated with/without exenatide during 8-week study period. The frequencies of Th17 and Treg cells from peripheral blood and pancreas in db/db mice were assessed. The phosphoinositide 3-kinase (PI3K)/protein kinase B (Akt)/Forkhead box O1 (FoxO1) pathway in Th17 and Treg cells from the spleens of male C57BL/6J mice was detected by western blotting. In addition, the expression of glucagon-like peptide-1 receptor (GLP-1R) in peripheral blood mononuclear cells (PBMCs) of male C57BL/6J mice was analyzed. Results: Exenatide treatment improved β-cell function and insulitis in addition to glucose, insulin sensitivity and weight. Increased Th17 and decreased Treg cells in peripheral blood were present as diabetes progressed while exenatide corrected this imbalance. Progressive IL-17 + T cell infiltration of pancreatic islets was alleviated by exenatide intervention. In vitro study showed no significant difference in the level of GLP-1R expression in PBMCs between control and palmitate (PA) groups. In addition, PA could promote Th17 but suppress Treg differentiation along with down-regulating the phosphorylation of PI3K/Akt/FoxO1, which was reversed by exenatide intervention. FoxO1 inhibitor AS1842856 could abrogate all these effects of exenatide against lipid stress. Conclusions: Exenatide could restore systemic Th17/Treg balance via regulating FoxO1 pathway with the progression of diabetes in db/db mice. The protection of pancreatic β-cell function may be partially mediated by inhibiting Th17 cell infiltration into pancreatic islets, and the resultant alleviation of islet inflammation. [ABSTRACT FROM AUTHOR]

Immunoglobin G4 (IgG4)-related disease in the eye and ocular adnexa (IgG4-ROD) is a newly discovered autoimmune disease that histologically exhibits extensive lymphocyte and plasma cell infiltration, occlusive phlebitis, and mat or whorled fibrosis. The disease can affect multiple ocular tissues and organs, such as the lacrimal gland, extraocular muscles, orbital fat, and trigeminal nerve. The main clinical manifestations are chronic, painless swelling of the orbit or unilateral orbit and proptosis, which may be accompanied by peripheral lymphadenopathy. Usually, visual impairment is not apparent, but in severe cases, it can cause a loss of function of the tissues and organs involved and affect the daily lives of patients. The pathogenesis of IgG4-ROD is not clear. Based on existing literature, it is speculated that it may be related to factors such as autoantibody production, microbial infection, and genetic inheritance. For the treatment of IgG4-ROD, glucocorticoids, immunosuppressive agents, biological agents, and surgery are mainly used in clinical practice. Although these treatment methods can achieve a particular effect, they have limitations, such as high recurrence rates, serious side effects, and postoperative complications. With the increase in IgG4-ROD-related reports, some progress has been made in the current understanding and research of the disease. [ABSTRACT FROM AUTHOR]

Ship detection in synthetic aperture radar (SAR) images is a significant and challenging task. However, most existing deep learning-based SAR ship detection approaches are confined to single-polarization SAR images and fail to leverage dual-polarization characteristics, which increases the difficulty of further improving the detection performance. One problem that requires a solution is how to make full use of the dual-polarization characteristics and how to excavate polarization features using the ship detection network. To tackle the problem, we propose a group-wise feature enhancement-and-fusion network with dual-polarization feature enrichment (GWFEF-Net) for better dual-polarization SAR ship detection. GWFEF-Net offers four contributions: (1) dual-polarization feature enrichment (DFE) for enriching the feature library and suppressing clutter interferences to facilitate feature extraction; (2) group-wise feature enhancement (GFE) for enhancing each polarization semantic feature to highlight each polarization feature region; (3) group-wise feature fusion (GFF) for fusing multi-scale polarization features to realize polarization features' group-wise information interaction; (4) hybrid pooling channel attention (HPCA) for channel modeling to balance each polarization feature's contribution. We conduct sufficient ablation studies to verify the effectiveness of each contribution. Extensive experiments on the Sentinel-1 dual-polarization SAR ship dataset demonstrate the superior performance of GWFEF-Net, with 94.18% in average precision (AP), compared with the other ten competitive methods. Specifically, GWFEF-Net can yield a 2.51% AP improvement compared with the second-best method. [ABSTRACT FROM AUTHOR]

Diverse pectinolytic enzymes are widely applied in the food, papermaking, and other industries, and they account for more than 25% of the global industrial enzyme demands. Efficient lignocellulose degradation microbiota are reservoirs of pectinolytic enzymes and other lignocellulose-degrading genes. Metagenomics has been widely used to discover new pectinolytic enzymes. Here, we used a metagenomic strategy to characterize pectinolytic genes from one efficient lignocellulose-degrading microbiota derived from pulp and paper wastewater treatment microbiota. A total of 23 predicted full-length GH28 and PL1 family pectinolytic genes were selectively cloned and expressed in Escherichia coli, and 5 of the expressed proteins had pectinolytic activities. Among them, the characterization of one pectinolytic enzyme, PW-pGH28-3, which has a 58.4% identity with an exo-polygalacturonase gene of Aquipluma nitroreducens, was further investigated. The optimal pH and optimal temperature of PW-pGH28-3 were 8.0 and 40 °C, respectively, and its pectinolytic activity at the optimal condition was 13.5 ± 1.1 U/mg protein. Bioinformatics analyses and structural modeling suggest that PW-pGH28-3 is a novel secretory exo-polygalacturonase, which is confirmed by its hydrolysates of polygalacturonic acid. The detection of PW-pGH28-3 and other pectinolytic genes showed that efficient lignocellulose degradation microbiota could provide potential efficient pectinolytic enzymes for industrial application. In the future, improving metagenomic screening efficiency would discover efficient lignocellulose-degrading enzymes and lead to the sustainable and green utilization of lignocellulose. [ABSTRACT FROM AUTHOR]

Objectives: The purpose of this study was to explore the clinical application value of phase angle (PA) of six parts in the nutritional evaluation and construct a prediction model for diagnosing malnutrition of tumor patients.Methods: A total of 1129 patients with malignant tumors were analyzed retrospectively. The age, sex, tumor location and body mass index (BMI) of the patients were collected, and PA of six parts was measured. The Patient Subjective Global Assessment (PG-SGA) was used to evaluate the nutritional status of each patient.Results: According to the PG-SGA, 66.5% (n = 750) of the patients were evaluated as malnourished. Patients under the age of 65 had higher PA values. The PA value of men was higher than that of women (except PA-RL). In different disease groups, the PA-RA and PA-TR values were significantly different. In our study, PA value increases with BMI and decreases with PG-SGA (except PG-SGA 0-1 group). Multivariate regression analysis indicates that the age (HR = 1.051, 95% CI 1.037-1.066, P < 0.001), BMI (HR = 0.885, 95% CI 0.849-0.924, P < 0.001), and PA-WB (HR = 0.615, 95% CI 0.546-0.692, P < 0.001) were independent significant predictors associated with malnutrition. The AUC of the prediction model is 0.7631 (p < 0.001), indicating that the model including age, BMI, and PA-WB has certain diagnostic value for the diagnosis of malnutrition.Conclusion: The PA-WB is an independent prognostic factor of malnutrition. The prediction model constructed by age, BMI, and PA-WB can be used as a useful tool for nutritional evaluation of tumor patients.Trial Registration: Clinical Trial No.: ChiCTR2100047858. [ABSTRACT FROM AUTHOR]

Summary: RPA2A is a subunit of the conserved heterotrimeric replication protein A (RPA) in Arabidopsis, which is an essential replisome component that binds to single‐stranded DNA during DNA replication. RPA2A controls a set of developmental processes, but the underlying mechanism is largely unknown.Here we show that RPA2A represses key flowering genes including FLOWERING LOCUS T (FT), AGAMOUS (AG) and AGAMOUS LIKE 71 (AGL71) to suppress floral transition by cooperating with the PRC2 complex.RPA2A is vigorously expressed in dividing cells and required for correct DNA replication. Mutation of RPA2A leads to early flowering, which is dependent on ectopic expression of key flowering genes including FT molecularly and genetically. RPA2A and PRC2 have common target genes including FT, AG and AGL71 supported using genetic analysis, transcriptome profiling and H3K27me3 ChIP‐seq analysis. Furthermore, RPA2A physically interacts with PRC2 components CLF, EMF2 and MSI1, which recruits CLF to the chromatin loci of FT, AG and AGL71.Together, our results show that the replication protein RPA2A recruits PRC2 to key flowering genes through physical protein interaction, thereby repressing the expression of these genes to suppress floral transition in Arabidopsis. [ABSTRACT FROM AUTHOR]

Purpose: Pyrotinib, a novel human epidermal growth factor receptor 2 (HER2)-targeted tyrosine kinase inhibitor (TKI), has led to remarkable survival outcomes in HER2-positive advanced breast cancer (ABC) in clinical trials and was approved for second-line standards of treatment for HER2+ ABC in China. However, the clinical trials could not fully reflect reality of clinical practice, and predictive factors were still lacking. This study aimed to assess the actual efficacy and safety of pyrotinib in HER2+ ABC in real-world setting. Patients and Methods: In this multicenter, retrospective, observational real-world study, we analyzed 171 patients with HER2+ ABC, who received pyrotinib-based treatment from November 2017 to November 2020. The primary end point was progression-free survival (PFS). Secondary end points included overall survival (OS), objective response rate (ORR), clinical benefit rate (CBR) and safety. Results: Up to November 30, 2021, the median PFS (mPFS) was 12.0 months for all patients. One hundred and sixty-two patients (94.7%) with measurable lesions had been included in efficacy assessment. The ORR and CBR were 45.1% and 81.5%, respectively. A significantly longer PFS was reported in patients who received pyrotinib as first-line treatment, had the ECOG-PS of 0– 1, as well as those who were lapatinib-naive. In addition, multivariable analysis indicated that ECOG-PS of 2– 4, positive hormone receptor (HR) status, and presence of visceral metastasis were independent negative predictors of PFS. As far as we know, this study first reported the survival outcome of pyrotinib cross-line treatment, with a mPFS of 5.0 months. All grades of adverse events (AEs) occurred in 171 patients (100%), and the most common AE was diarrhea (86.5%). Conclusion: This study further demonstrated the outstanding efficacy and safety of pyrotinib and reported the potential predictors of survival in HER2+ ABC. [ABSTRACT FROM AUTHOR]

Objective. To compare the clinical efficacy and adverse drug reactions of four different schemes in the treatment of pleural tuberculoma. Methods. A total of 120 patients with pleural tuberculoma admitted to the Tuberculosis Department of our hospital from January 2018 to January 2021 were selected as the research subjects. According to different treatment methods, the patients were divided into four groups, with 30 cases in each group. They were as follows: group A received classical HRZE regimen, group B received HRZE+pleural injection, group C received HZE+rifabutin, and group D received HZE+rifabutin+pleural injection. All patients were treated intensively for 3 months and then consolidated treatment for 6 months according to the patient's condition. The absorption of lesions in the four groups at different time was compared, and the occurrences of adverse drug reactions and treatment outcomes during treatment were recorded. Results. After 3 months of treatment, compared with groups A, B, and C, the number of significantly absorbed cases and effective cases in group D increased, while the number of invalid cases decreased. However, there was no statistical significance in the absorption of lesions between the four groups ( χ 2 = 8.272 , P = 0.507). In addition, pairwise comparison showed no significant difference in the absorption of lesions (P > 0.05). After 9 months of treatment, there was no significant difference in the absorption of lesions among the four groups ( χ 2 = 8.795 , P = 0.185), but the absorption of lesions in group D was significantly better than that in group A (P < 0.05). During treatment, the incidence of adverse reactions in the four groups was significantly different ( χ 2 = 8.779 , P = 0.032). Pairwise comparison showed that the incidence of adverse reactions in groups C and D was significantly lower than that in group A (P < 0.05). The total treatment course of group A was 9-16 months, and 10 cases (33.33%) still had residual lesions or pleural thickening at the end of treatment. The total course of treatment in group B was 9-12 months, and 7 cases (23.33%) still had residual lesions or pleural thickening at the end of the course of treatment. The total treatment course of group C was 9-16 months, and 8 cases (26.67%) still had residual lesions or pleural thickening at the end of treatment. The total course of treatment in group D was 9-12months, and there were still 2 cases of residual lesions (6.67%) at the end of the course. Conclusions. HZE+rifabutin+pleural injection against tuberculosis therapy has a significant clinical efficacy in the treatment of pleural tuberculoma, which can more effectively improve the clinical symptoms of patients, improve the efficacy, and reduce complications, with a good prognosis, worthy of clinical promotion. [ABSTRACT FROM AUTHOR]

A correction to the article "BMC Palliat Care 23, 136 (2024)" in the BMC Palliative Care issue discusses the addition of equal contribution acknowledgment for the first and second authors, Guojuan Chen and Xiaoling Zhang.

Ship detection with rotated bounding boxes in synthetic aperture radar (SAR) images is now a hot spot. However, there are still some obstacles, such as multi-scale ships, misalignment between rotated anchors and features, and the opposite requirements for spatial sensitivity of regression tasks and classification tasks. In order to solve these problems, we propose a rotated balanced feature-aligned network (RBFA-Net) where three targeted networks are designed. They are, respectively, a balanced attention feature pyramid network (BAFPN), an anchor-guided feature alignment network (AFAN) and a rotational detection network (RDN). BAFPN is an improved FPN, with attention module for fusing and enhancing multi-level features, by which we can decrease the negative impact of multi-scale ship feature differences. In AFAN, we adopt an alignment convolution layer to adaptively align the convolution features according to rotated anchor boxes for solving the misalignment problem. In RDN, we propose a task decoupling module (TDM) to adjust the feature maps, respectively, for solving the conflict between the regression task and classification task. In addition, we adopt a balanced L1 loss to balance the classification loss and regression loss. Based on the SAR rotation ship detection dataset, we conduct extensive ablation experiments and compare our RBFA-Net with eight other state-of-the-art rotated detection networks. The experiment results show that among the eight state-of-the-art rotated detection networks, RBFA-Net makes a 7.19% improvement with mean average precision compared to the second-best network. [ABSTRACT FROM AUTHOR]

Highly convection-related short-duration heavy rainfall (SDHR), defined as rainfall greater than 20 mm h−1 of a whole hour, causes severe damage every year in China. An objective forecasting method is developed to provide guidance products for the short-term probability of SDHR. Representative parameters of environmental moisture content, instability, and dynamical forcing are selected as predictors based on the ingredients-based methodology. The predictors are selected by comparing their ability to discriminate between SDHR and both no rainfall and ordinary rainfall with hourly rainfall records and the NCEP reanalysis dataset during the warm seasons of 2002 and 2009. A fuzzy logic approach is obtained for the calculation of SDHR probability. Intervals of intensities are obtained based on specific percentiles and various weight settings examined. The probabilistic SDHR forecasts during the 2015 warm seasons with the NCEP GFS dataset are obtained, and forecasts are evaluated by using an operational used spatial verification method. Results show that the reference operational SDHR forecasts are surpassed by the 00–12 h period objective SDHR forecasts measured with the maximum critical success index (CSI), and even the average CSI (CSIave) for the top groups is better than the reference. The guidance SDHR products are skillful within 60 h. Although the weights vary significantly, the short-term patterns of the SDHR probability are mainly determined by the environmental conditions. The objective forecasting method is ingredients-based but is combined with fuzzy logic algorithms. The new approach provides a feasible exploration of the convective weather phenomenon. [ABSTRACT FROM AUTHOR]

Introduction: Patients with acute isolated vertigo have a high risk for developing cerebral infarction (CI). Risk stratification for cerebral infarction in patients with acute isolated vertigo is critical for early treatment and preventative therapy. In the present study, we aim to characterize the diagnostic value of serum adiponectin (APN) combined with ABCD2 scoring in determining cerebral infarction risk. Methods: Patients with acute isolated vertigo admitted to the emergency room were recruited. Diagnosis of cerebral infarction was performed using diffusion-weighted MRI (DWI-MRI) and T2WI and T2Flair imaging. Blood was collected for analysis of APN levels using enzyme-linked immunosorbent assay (ELISA). Multivariate analysis was used to analyze diabetes, hypertension, serum APN, and ABCD2 in association with CI. Results: Compared to non-CI patients (n = 185), patients with CI (n = 68) demonstrated significantly lower serum APN levels (p < 0.001) and higher ABCD2 score (p < 0.001). A strong negative correlation was found between serum APN levels and ABCD2 scores. Multivariate analysis and ROC analysis suggested that low serum APN and high ABCD2 are strong predictors of CI in patients with acute isolated vertigo. Notably, the combination of APN and ABCD2 had a much stronger predictive sensitivity and specificity. Conclusion: Our analysis suggests that the combination of serum APN and ABCD2 analyses offers a significantly improved prediction sensitivity and specificity for CI among patients with acute and isolated vertigo, which supports the potential use of this new marker in clinics. [ABSTRACT FROM AUTHOR]

Phase filtering is a vital step for interferometric synthetic aperture radar (InSAR) terrain elevation measurements. Existing phase filtering methods can be divided into two categories: traditional model-based and deep learning (DL)-based. Previous studies have shown that DL-based methods are frequently superior to traditional ones. However, most of the existing DL-based methods are purely data-driven and neglect the filtering model, so that they often need to use a large-scale complex architecture to fit the huge training sets. The issue brings a challenge to improve the accuracy of interferometric phase filtering without sacrificing speed. Therefore, we propose a sparse-model-driven network (SMD-Net) for efficient and high-accuracy InSAR phase filtering by unrolling the sparse regularization (SR) algorithm to solve the filtering model into a network. Unlike the existing DL-based filtering methods, the SMD-Net models the physical process of filtering in the network and contains fewer layers and parameters. It is thus expected to ensure the accuracy of the filtering without sacrificing speed. In addition, unlike the traditional SR algorithm setting the spare transform by handcrafting, a convolutional neural network (CNN) module was established to adaptively learn such a transform, which significantly improved the filtering performance. Extensive experimental results on the simulated and measured data demonstrated that the proposed method outperformed several advanced InSAR phase filtering methods in both accuracy and speed. In addition, to verify the filtering performance of the proposed method under small training samples, the training samples were reduced to 10%. The results show that the performance of the proposed method was comparable on the simulated data and superior on the real data compared with another DL-based method, which demonstrates that our method is not constrained by the requirement of a huge number of training samples. [ABSTRACT FROM AUTHOR]

Existing instance segmentation models mostly pay less attention to the targeted characteristics of ships in synthetic aperture radar (SAR) images, which hinders further accuracy improvements, leading to poor segmentation performance in more complex SAR image scenes. To solve this problem, we propose a hybrid task cascade plus (HTC+) for better SAR ship instance segmentation. Aiming at the specific SAR ship task, seven techniques are proposed to ensure the excellent performance of HTC+ in more complex SAR image scenes, i.e., a multi-resolution feature extraction network (MRFEN), an enhanced feature pyramid net-work (EFPN), a semantic-guided anchor adaptive learning network (SGAALN), a context ROI extractor (CROIE), an enhanced mask interaction network (EMIN), a post-processing technique (PPT), and a hard sample mining training strategy (HSMTS). Results show that each of them offers an observable accuracy gain, and the instance segmentation performance in more complex SAR image scenes becomes better. On two public datasets SSDD and HRSID, HTC+ surpasses the other nine competitive models. It achieves 6.7% higher box AP and 5.0% higher mask AP than HTC on SSDD. These are 4.9% and 3.9% on HRSID. [ABSTRACT FROM AUTHOR]

Synthetic aperture radar (SAR) is an advanced microwave sensor, which has been widely used in ocean surveillance, and its operation is not affected by light and weather. SAR ship instance segmentation can provide not only the box-level ship location but also the pixel-level ship contour, which plays an important role in ocean surveillance. However, most existing methods are provided with limited box positioning ability, hence hindering further accuracy improvement of instance segmentation. To solve the problem, we propose a global context boundary-aware network (GCBANet) for better SAR ship instance segmentation. Specifically, we propose two novel blocks to guarantee GCBANet's excellent performance, i.e., a global context information modeling block (GCIM-Block) which is used to capture spatial global long-range dependences of ship contextual surroundings, enabling larger receptive fields, and a boundary-aware box prediction block (BABP-Block) which is used to estimate ship boundaries, achieving better cross-scale box prediction. We conduct ablation studies to confirm each block's effectiveness. Ultimately, on two public SSDD and HRSID datasets, GCBANet outperforms the other nine competitive models. On SSDD, it achieves 2.8% higher box average precision (AP) and 3.5% higher mask AP than the existing best model; on HRSID, they are 2.7% and 1.9%, respectively. [ABSTRACT FROM AUTHOR]

Nearfield (NF) 3-D imaging provides an effective solution of objects’ radar cross section (RCS) within a compact range. This article proposes a precise RCS extrapolation via NF 3-D imaging with adaptive parameter optimization Bayesian learning (APOBL), i.e., first, in the process of NF 3-D imaging, objects’ scattering centers may vary with the observation angle, while it is hard for the existing Bayesian learning via presetting parameters to reach an optimal estimation. For this issue, we present a parameter self-adaption solution, improving precision, and stability. Second, we also apply a block-based optimization idea in Bayesian-learning-based 3-D imaging, ensuring NF 3-D imaging quality. Third, in the process of RCS extrapolation, we apply a weighted Green’s function operator into the 3-D imaging-based NF-to-far-field (NF–FF) compensation, further ensuring high precision. The simulation and experiment results verify that the proposed method has an advantage in precision over the existing 3-D imaging-based RCS extrapolation methods. [ABSTRACT FROM AUTHOR]

A multiview clustering (MVC) has been a significant technique to dispose data mining issues. Most of the existing studies on this topic adopt a fixed number of neighbors when constructing the similarity matrix of each view, like single-view clustering. However, this may reduce the clustering effect due to the diversity of multiview data sources. Moreover, most MVC utilizes iterative optimization to obtain clustering results, which consumes a significant amount of time. Therefore, this paper proposes a multiview clustering of adaptive sparse representation based on coupled P system (MVCS-CP) without iteration. The whole algorithm flow runs in the coupled P system. Firstly, the natural neighbor search algorithm without parameters automatically determines the number of neighbors of each view. In turn, manifold learning and sparse representation are employed to construct the similarity matrix, which preserves the internal geometry of the views. Next, a soft thresholding operator is introduced to form the unified graph to gain the clustering results. The experimental results on nine real datasets indicate that the MVCS-CP outperforms other state-of-the-art comparison algorithms. [ABSTRACT FROM AUTHOR]

Aims: This study evaluates the safety and preliminary antitumor efficacy of camrelizumab with albumin-binding paclitaxel and cisplatin as first-line therapy for patients with recurrent or metastatic cervical carcinoma.Methods and Material: In this phase 2, open-label, prospective study, 35 patients with recurrent or metastatic cervical carcinoma with no previous systemic chemotherapy were included. The patients were treated with a maximum of six cycles of camrelizumab on day 1, albumin-binding paclitaxel, and carboplatin on day 2, every 3 weeks, followed by camrelizumab once every 3 weeks. The primary outcomes were objective response rate (ORR) and disease control rate (DCR). Secondary outcomes were duration of response (DoR) and safety. Furthermore, 27 patients were included in the per-protocol set for efficacy analysis, whereas for the safety analysis, all patients were included.Results: The median follow-up was 4.53 months, and the complete response, partial response, and stable disease were also achieved in 4 (14.81%), 6 (22.22%), and 13 (48.15%) patients. The ORR and DCR were 40.00% (95% confidence interval: 21.13-61.33%) and 92.00% (73.97-99.01%), respectively. The median DoR was 6.70 months. In addition, the most common adverse events (AEs) were reactive cutaneous capillary endothelial proliferation (RCCEP) (23, 65.71%), gastrointestinal reaction (8, 22.86%), and fever (8, 22.86%). Grade 3 AEs included 5 (14.29%) myelosuppression, and grade 4 AEs included 1 (2.86%) RCCEP and 1 (2.86%) bladder inflammation.Conclusions: Combination therapy of camrelizumab and albumin-bound paclitaxel and carboplatin shows promising efficacy and manageable toxicities in patients with recurrent or metastatic cervical cancer. [ABSTRACT FROM AUTHOR]

Bookmarks are the basis for librarians to get books on and off shelves and borrowers to borrow books. In order to solve the problem of time-consuming and labor-consuming manual checking of bookmark aging, this paper proposes a method of bookmark aging recognition based on image processing technology. First, we perform image preprocessing, Otsu threshold segmentation, and morphological processing on the acquired bookmark image to obtain the effective area of the bookmark, then acquire the aging features for the bookmark, and finally input the acquired features into the trained neural network for defect recognition. The experimental results show that the method proposed in this paper can achieve 96% recognition, which can more accurately identify the aging defects of bookmarks. [ABSTRACT FROM AUTHOR]